A Realistic and Stable Markov-based Model for WSNs

Certain Wireless Sensor Network (WSN) applications such as patient monitoring, smart grid and equipment condition monitoring require accurate estimation of specific WSN parameters such as the end-to-end delay, the reliability and the power consumption. The estimation of these parameters calls for an accurate and lightweight WSN model that is suitable for the low processing capabilities of sensor nodes. In this paper, we present a realistic and stable Markov based model for WSNs. We perform a comprehensive performance analysis using different traffic and network conditions. Furthermore, we test the accuracy of our model by conducting extensive simulations in environments that are equivalent to the analytical model. The proposed model takes into account the traffic generation probabilities and considers the impact of a finite MAC-level buffer size on the end-to-end delay, reliability and power consumption.